2021
DOI: 10.1021/acssensors.1c00628
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Dynamic Imaging and Characterization of Volatile Aerosols in E-Cigarette Emissions Using Deep Learning-Based Holographic Microscopy

Abstract: Various volatile aerosols have been associated with adverse health effects; however, characterization of these aerosols is challenging due to their dynamic nature. Here, we present a method that directly measures the volatility of particulate matter (PM) using computational microscopy and deep learning. This method was applied to aerosols generated by electronic cigarettes (e-cigs), which vaporize a liquid mixture (e-liquid) that mainly consists of propylene glycol (PG), vegetable glycerin (VG), nicotine, and … Show more

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Cited by 19 publications
(10 citation statements)
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“…36 However, currently, both these smartphone-based and lensfree holographic devices are limited in resolution to particles larger than 1 μm, [30][31][32]35 or in some cases, particles larger than 500 nm. 36 In some of our prior work, we have optimized lensfree holographic microscopy for nanoparticle detection, but have not applied this to aerosolized particulate matter sensing. 37−41 Other optical-based systems measure the change in transmission as particles adhere 42 or pass through 43 a fiber and can detect particles smaller than 1 μm.…”
Section: ■ Introductionmentioning
confidence: 99%
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“…36 However, currently, both these smartphone-based and lensfree holographic devices are limited in resolution to particles larger than 1 μm, [30][31][32]35 or in some cases, particles larger than 500 nm. 36 In some of our prior work, we have optimized lensfree holographic microscopy for nanoparticle detection, but have not applied this to aerosolized particulate matter sensing. 37−41 Other optical-based systems measure the change in transmission as particles adhere 42 or pass through 43 a fiber and can detect particles smaller than 1 μm.…”
Section: ■ Introductionmentioning
confidence: 99%
“…This results in images with resolution comparable to lens-based systems over the whole field of view of the sensor. Previously, lensfree holographic devices have been used for air-quality monitoring and volatile aerosol characterization of e-cigarette smoke . However, currently, both these smartphone-based and lensfree holographic devices are limited in resolution to particles larger than 1 μm, , or in some cases, particles larger than 500 nm .…”
Section: Introductionmentioning
confidence: 99%
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“…One cascade impactor, Electrical Low Pressure Impactor (ELPI ® +), electrically charges the aerosol particles and with electrometers on each stage counts the number of particles in real time, removing the need for post gravimetric or chemical analysis, however density of the aerosol is required to convert the measured count median diameter to a mass median diameter that is provided directly by other cascade impactors. Recent work has attempted to identify (11), quantify (12,13) and determine the evaporation time course (14) for some of the volatile constituents of ENDS aerosol. BEREN-GUER et al (11) identified 34 volatile compounds in the ENDS aerosol they tested using standard analytical chemistry techniques (Headspace solid phase extraction + gas chromatography-mass spectrometry).…”
mentioning
confidence: 99%
“…LALO et al (12) used mass recovery efficiency from cascade impactor measurements to estimate the amount of volatilized nicotine which increased when the power was switched from low to high on the specific ENDS product they used. LUO et al (13) used an impactor stage to focus particle deposition on a transparent adhesive surface where digital pictures were recorded using a holographic microscope (2 frames/s) and reported rapid evaporation of propylene glycol that changed with the addition of nicotine or several flavors. Finally, laser-trapping (counter-propagating optical tweezers) and single particle Raman scattering was used to investigate the time course of nicotine and propylene glycol volatilization as well as water condensation on ENDS aerosol as a function of e-liquid pH (6).…”
mentioning
confidence: 99%